In many instances, machines such as for example electric motors, electric generators, internal-combustion engines, jet engines, turbines, and the like, the systems they drive, and processes are actively monitored by various monitoring systems for performance and operational characteristics including for example vibration, heat, noise, electrical characteristics (e.g., current, voltage, resistance, etc.), environmental effects, process parameters and the like. Generally, the monitoring systems that monitor these machines and processes are comprised of one or more transducers that are proximate to and associated with the machine or process. The monitoring systems can also include components for signal processing, alarming and display, which may be combined into one device or located in separate components. Recently, wireless transducers are being used in these monitoring systems to facilitate installation and reduce wiring “congestion.” Currently, in some instances wireless transducer systems periodically “wake up” and take one or more readings on some parameter associated with the machine or process with which they are associated. When the sensor wakes up, it is generally done so on a time or periodic basis and in some instances the machine or process may not be running when the sensor becomes active. At worst, capturing monitoring data during times of non-operation of the machine or process can lead to an alarm because the sensor reading is not what is expected, or at least can cause waste of the storage space for the data since if it is not taken while the machine or process is not running then it may not have any value.
Often data from these types of monitoring systems is provided to an automated system that performs rudimentary data analysis without operator interference. The ability for these automated systems to know the operating state of the machine or process when the data was collected can be very useful to insure data comparisons are under similar operating conditions. Not knowing the operating state of the machine or process when the data was collected can also lead to confusion in data analysis because the viewer of the data has no way of knowing (in many cases) the operating state of the machine or process when the data was collected.
Previous attempts to address this issue include utilizing a keyphasor or other direct measurement of rotor speed of the machine. While this is a completely robust and well understood solution to defining when a machine is in operation, it is also very expensive because it involves a great deal of installation effort plus the cost of the extra transducer and wiring necessary to power that transducer. Additionally, there have been some efforts to identify the operation mode of machinery by recognizing the signature present in vibration or other signals associated with the motors. While these methods work in some instances, there exists the possibility of false positives and vibration signatures may not be present on smoothly operating machines.
Therefore, systems and methods that overcome challenges in the art, some of which are described above, are desired. In particular, providing a sure indication of machine or process status would be valuable in addressing the above-described challenges.